Domenic Ravita, SingleStore | AWS re:Invent 2022
>>Hey guys and girls, welcome back to The Cube's Live coverage of AWS Reinvent 22 from Sin City. We've been here, this is our third day of coverage. We started Monday night first. Full day of the show was yesterday. Big news yesterday. Big news. Today we're hearing north of 50,000 people, and I'm hearing hundreds of thousands online. We've been having great conversations with AWS folks in the ecosystem, AWS customers, partners, ISVs, you name it. We're pleased to welcome back one of our alumni to the program, talking about partner ecosystem. Dominic Rav Vida joins us, the VP of Developer relations at single store. It's so great to have you on the program. Dominic. Thanks for coming. >>Thanks. Great. Great to see you >>Again. Great to see you too. We go way back. >>We do, yeah. >>So let's talk about reinvent 22. This is the 11th reinvent. Yeah. What are some of the things that you've heard this week that are exciting that are newsworthy from single stores perspective? >>I think in particular what we heard AWS announce on the zero ETL between Aurora and Redshift, I think it's, it's significant in that AWS has provided lots of services for building blocks for applications for a long time. And that's a great amount of flexibility for developers. But there are cases where, you know, it's a common thing to need to move data from transactional systems to analytics systems and making that easy with zero etl, I think it's a significant thing and in general we see in the market and especially in the data management market in the cloud, a unification of different types of workloads. So I think that's a step in the right direction for aws. And I think for the market as a whole, why it's significant for single store is, that's our specialty in particular, is to unify transactions and analytics for realtime applications and analytics. When you've got customer facing analytic applications and you need low latency data from realtime streaming data sources and you've gotta crunch and compute that. Those are diverse types of workloads over document transactional workloads as well as, you know, analytical workloads of various shapes and the data types could be diverse from geospatial time series. And then you've gotta serve that because we're all living in this digital service first world and you need that relevant, consistent, fresh data. And so that unification is what we think is like the big thing in data right >>Now. So validation for single store, >>It does feel like that. I mean, I'd say in the recent like six months, you've seen announcements from Google with Alloy db basically adding the complement to their workload types. You see it with Snowflake adding the complement to their traditional analytical workload site. You see it with Mongo and others. And yeah, we do feel it was validation cuz at single store we completed the functionality for what we call universal storage, which is, is the industry's first third type of storage after row store and column store, single store dbs, universal storage, unifies those. So on a single copy of data you can form these diverse workloads. And that was completed three years ago. So we sort of see like, you know, we're onto something >>Here. Welcome to the game guys. >>That's right. >>What's the value in that universal storage for customers, whether it's a healthcare organization, a financial institution, what's the value in it in those business outcomes that you guys are really helping to fuel? >>I think in short, if there were like a, a bumper sticker for that message, it's like, are you ready for the next interaction? The next interaction with your customer, the next interaction with your supply chain partner, the next interaction with your internal stakeholders, your operational managers being ready for that interaction means you've gotta have the historical data at the ready, accessible, efficiently accessible, and and, and queryable along with the most recent fresh data. And that's the context that's expected and be able to serve that instantaneously. So being ready for that next interaction is what single store helps companies do. >>Talk about single store helping customers. You know, every company these days has to be a data company. I always think, whether it's my grocery store that has all my information and helps keep me fed or a gas station or a car dealer or my bank. And we've also here, one of the things that John Furrier got to do, and he does this every year before aws, he gets to sit down with the CEO and gets really kind of a preview of what's gonna happen at at the show, right? And Adams Lisky said to him some interesting very poignant things. One is that that data, we talk about data democratization, but he says the role of the data analyst is gonna go away. Or that maybe that term in, in that every person within an organization, whether you're marketing, sales, ops, finance, is going to be analyzing data for their jobs to become data driven. Right? How does single store help customers really become data companies, especially powering data intensive apps like I know you do. >>Yeah, that's, there's a lot of talk about that and, and I think there's a lot of work that's been done with companies to make that easier to analyze data in all these different job functions. While we do that, it's not really our starting point because, and our starting point is like operationalizing that analytics as part of the business. So you can think of it in terms of database terms. Like is it batch analysis? Batch analytics after the fact, what happened last week? What happened last month? That's a lot of what those data teams are doing and those analysts are doing. What single store focuses more is in putting those insights into action for the business operations, which typically is more on the application side, it's the API side, you might call it a data product. If you're monetizing your data and you're transacting with that providing as an api, or you're delivering it as software as a service, and you're providing an end-to-end function for, you know, our marketing marketer, then we help power those kinds of real time data applications that have the interactivity and have that customer touchpoint or that partner touchpoint. So you can say we sort of, we put the data in action in that way. >>And that's the most, one of the most important things is putting data in action. If it's, it can be gold, it can be whatever you wanna call it, but if you can't actually put it into action, act on insights in real time, right? The value goes way down or there's liability, >>Right? And I think you have to do that with privacy in mind as well, right? And so you have to take control of that data and use it for your business strategy And the way that you can do that, there's technology like single store makes that possible in ways that weren't possible before. And I'll give you an example. So we have a, a customer named Fathom Analytics. They provide web analytics for marketers, right? So if you're in marketing, you understand this use case. Any demand gen marketer knows that they want to see what the traffic that hits their site is. What are the page views, what are the click streams, what are the sequences? Have these visitors to my website hit certain goals? So the big name in that for years of course has been Google Analytics and that's a free service. And you interact with that and you can see how your website's performing. >>So what Fathom does is a privacy first alternative to Google Analytics. And when you think about, well, how is that possible that they, and as a paid service, it's as software, as a service, how, first of all, how can you keep up with that real time deluge of clickstream data at the rate that Google Analytics can do it? That's the technical problem. But also at the data layer, how could you keep up with Google has, you know, in terms of databases And Fathom's answer to that is to use single store. Their, their prior architecture had four different types of database technologies under the hood. They were using Redis to have fast read time cash. They were using MySEQ database as the application database they were using. They were looking at last search to do full tech search. And they were using DynamoDB as part of a another kind of fast look up fast cash. They replaced all four of those with single store. And, and again, what they're doing is like sort of battling defacto giant in Google Analytics and having a great success at doing that for posting tens of thousands of websites. Some big names that you've heard of as well. >>I can imagine that's a big reduction from four to one, four x reduction in databases. The complexities that go away, the simplification that happens, I can imagine is quite huge for them. >>And we've done a study, an independent study with Giga Home Research. We published this back in June looking at total cost of ownership with benchmarks and the relevant benchmarks for transactions and analytics and databases are tpcc for transactions, TPC H for analytics, TPC DS for analytics. And we did a TCO study using those benchmark datas on a combination of transactional and analytical databases together and saw some pretty big improvements. 60% improvement over Myse Snowflake, for >>Instance. Awesome. Big business outcomes. We only have a few seconds left, so you've already given me a bumper sticker. Yeah. And I know I live in Silicon Valley, I've seen those billboards. I know single store has done some cheeky billboard marketing campaigns. But if you had a new billboard to create from your perspective about single store, what does it say? >>I, I think it's that, are you, are you ready for the next interaction? Because business is won and lost in every moment, in every location, in every digital moment passing by. And if you're not ready to, to interact and transact rather your systems on your behalf, then you're behind the curve. It's easy to be displaced people swipe left and pick your competitor. So I think that's the next bumper sticker. I may, I would say our, my favorite billboard so far of what we've run is cover your SaaS, which is what is how, what is the data layer to, to manage the next level of SaaS applications, the next generation. And we think single store is a big part >>Of that. Cover your SaaS. Love it. Dominic, thank you so much for joining me, giving us an update on single store from your perspective, what's going on there, kind of really where you are in the market. We appreciate that. We'll have to >>Have you back. Thank you. Glad to >>Be here. All right. For Dominic rta, I'm Lisa Martin. You're watching The Cube, the leader in live, emerging and enterprise tech coverage.
SUMMARY :
It's so great to have you on the program. Great to see you Great to see you too. What are some of the things that you've heard this week that are exciting that are newsworthy from And so that unification is what we think is like the So on a single copy of data you can form these diverse And that's the context that's expected and be able to serve that instantaneously. one of the things that John Furrier got to do, and he does this every year before aws, he gets to sit down with the CEO So you can think of it in terms of database terms. And that's the most, one of the most important things is putting data in action. And I think you have to do that with privacy in mind as well, right? But also at the data layer, how could you keep up with Google has, you know, The complexities that go away, the simplification that happens, I can imagine is quite huge for them. And we've done a study, an independent study with Giga Home Research. But if you had a new billboard to create from your perspective And if you're not ready to, to interact and transact rather your systems on Dominic, thank you so much for joining me, giving us an update on single store from your Have you back. the leader in live, emerging and enterprise tech coverage.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dominic | PERSON | 0.99+ |
Lisa Martin | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
60% | QUANTITY | 0.99+ |
Silicon Valley | LOCATION | 0.99+ |
Sin City | LOCATION | 0.99+ |
June | DATE | 0.99+ |
Today | DATE | 0.99+ |
last week | DATE | 0.99+ |
yesterday | DATE | 0.99+ |
Monday night | DATE | 0.99+ |
last month | DATE | 0.99+ |
Giga Home Research | ORGANIZATION | 0.99+ |
ORGANIZATION | 0.99+ | |
John Furrier | PERSON | 0.99+ |
one | QUANTITY | 0.99+ |
third day | QUANTITY | 0.99+ |
single store | QUANTITY | 0.99+ |
Domenic Ravita | PERSON | 0.99+ |
Dominic Rav Vida | PERSON | 0.99+ |
Google Analytics | TITLE | 0.99+ |
Adams Lisky | PERSON | 0.99+ |
Fathom | ORGANIZATION | 0.98+ |
three years ago | DATE | 0.98+ |
single | QUANTITY | 0.98+ |
Fathom Analytics | ORGANIZATION | 0.98+ |
single copy | QUANTITY | 0.98+ |
hundreds of thousands | QUANTITY | 0.98+ |
Mongo | ORGANIZATION | 0.97+ |
One | QUANTITY | 0.97+ |
SingleStore | ORGANIZATION | 0.97+ |
this week | DATE | 0.97+ |
The Cube | TITLE | 0.96+ |
first third type | QUANTITY | 0.94+ |
four | QUANTITY | 0.94+ |
tens of thousands of websites | QUANTITY | 0.92+ |
MySEQ | TITLE | 0.91+ |
six months | QUANTITY | 0.91+ |
Redis | TITLE | 0.9+ |
DynamoDB | TITLE | 0.9+ |
Dominic rta | PERSON | 0.89+ |
Reinvent 22 | TITLE | 0.89+ |
north of 50,000 people | QUANTITY | 0.86+ |
first alternative | QUANTITY | 0.81+ |
first | QUANTITY | 0.81+ |
single stores | QUANTITY | 0.78+ |
first world | QUANTITY | 0.73+ |
Alloy | TITLE | 0.69+ |
few seconds | QUANTITY | 0.67+ |
Redshift | ORGANIZATION | 0.67+ |
Snowflake | ORGANIZATION | 0.67+ |
aws | ORGANIZATION | 0.67+ |
TCO | ORGANIZATION | 0.66+ |
Invent | EVENT | 0.66+ |
reinvent 22 | EVENT | 0.65+ |
Snowflake | TITLE | 0.65+ |
2022 | DATE | 0.64+ |
Aurora | ORGANIZATION | 0.56+ |
11th reinvent | EVENT | 0.52+ |
Fathom | PERSON | 0.51+ |
Myse | ORGANIZATION | 0.49+ |
Cube | ORGANIZATION | 0.46+ |
zero | QUANTITY | 0.34+ |